Multicentric pilot study to standardize clinical whole exome sequencing (WES) for cancer patients
Michael Menzel, Stephan Ossowski, Sebastian Kral, Patrick Metzger, Peter Horak, Ralf Marienfeld, Melanie Boerries, Steffen Wolter, Markus Ball, Olaf Neumann, Sorin Armeanu–Ebinger, Christopher Schroeder, Uta Matysiak, Hannah Goldschmid, V. Schipperges, Axel Fürstberger, Michael Allgäuer, Timo Eberhardt, Jakob Niewöhner, Andreas Blaumeiser, Carolin Ploeger, Tobias B. Haack, Timothy Kwang Yong Tay, Olga Kelemen, Thomas Pauli, Martina Kirchner, Klaus Kluck, A. Ott, Marcus Renner, Jakob Admard, Axel Gschwind, Silke Laßmann, Hans A. Kestler, Falko Fend, Anna Lena Illert, Martin Werner, Peter Mӧller, Thomas Seufferlein, Nisar P. Malek, Peter Schirmacher, Stefan Fröhling, Daniel Kazdal, Jan Budczies, Albrecht Stenzinger
Abstract
A growing number of druggable targets and national initiatives for precision oncology necessitate broad genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a positive percentage agreement (PPA) between 91 and 95% and a positive predictive value (PPV) between 82 and 95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Explanations for deviations included low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.